High-Dimensional Uncertainty Visualization is a multivariate uncertainty visualization technique that specifically addresses the representation and interpretation of uncertainty in data spaces with a large number of dimensions, where conventional visual metaphors become ineffective due to the inherent complexity and interdependence of uncertain variables.
16
Publications
886
Citations
70
Authors
32
Institutions
Publications per year
2017–2026
5
Publications
16
Visualizing Summary Statistics and Uncertainty
Kristin Potter, Joe Kniss, Richard F. Riesenfeld et al. · Computer Graphics Forum · 2010 · 138 citations
Analysis of large-scale scalar data using hixels
David Thompson, Joshua A. Levine, Janine Camille Bennett et al. · 2011 · 82 citations
1–5 of 16
Authors
70
- VP
3
h-index
- CR
2
h-index
- PR
2
h-index
- KM
2
h-index
- KP
2
h-index
1–5 of 70
Institutions
32
University of Utah
Salt Lake City, United States
5 h-index
16 publications
1.7K citations
University of California, Davis
Davis, United States
3 h-index
5 publications
82 citations
Los Alamos National Laboratory
Los Alamos, United States
2 h-index
2 publications
37 citations
Lawrence Livermore National Laboratory
Livermore, United States
2 h-index
4 publications
451 citations
Zhejiang University of Technology
Hangzhou, China
1 h-index
1 publications
71 citations
Martin Luther University Halle-Wittenberg
Halle, Germany
1 h-index
2 publications
26 citations
Wright State University
Dayton, United States
1 h-index
1 publications
12 citations
Advanced Imaging Research (United States)
Cleveland, United States
1 h-index
2 publications
276 citations
1–8 of 32
Venues
- IEEE Transactions on Visualization and Computer Graphics
TVCG · 2 publications · 194 citations
2
h-index
- Computers & Geosciences
CAGEO · 2 publications · 70 citations
2
h-index
- Computer Graphics Forum
2 publications · 165 citations
2
h-index
- IEEE Computer Graphics and Applications
1 publications · 27 citations
1
h-index
- BMC Bioinformatics
1 publications · 11 citations
1
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1–5